- Monadic testing is a commonly used pricing research technique.
- Monadic testing is one of the least biased and most defensible ways to measure price sensitivity.
- There are several methodology variations of the monadic design (e.g. sequential monadic design, paired- comparison design and protomonadic design); which generally deal with the number of products respondents are exposed to.
Description of How it Works
- Respondents in a market research interview (i.e. phone, in-person or web) are asked to consider a complete set of products and to choose the one that best meets their needs. One of the factors to be considered is the product’s price.
- This method is monadic due to the fact that each respondent is exposed to only one price scenario in the study.
- The overall research study, however, will examine several different price points.
- To examine respondent’s reaction to different price points the total sample is split into separate sample cells.
- Each cell (i.e. sample group) is exposed to a different price point.
- By analyzing the respondent’s choices or rankings by cell an estimate of the product’s demand at the different price points can be created.
- A monadic design eliminates any respondent bias towards price testing. This is because they are exposed to only one price in the context of the total product offering. Respondents are unaware that price is the subject of the research.
- The analysis of monadic price test data produces information that provides strategic direction to marketing managers. It is helpful in developing forecasting models and testing different price points or structures.
- The research is not dynamic with respect to the competitive product’s prices. Changes in the competitive product’s prices could significantly change the predicted outcomes of the research.
- The sample size required for monadic tests is generally very large, due to the required sub-samples (i.e. cells). This makes the monadic design a relatively costly research method.
- When designing a monadic research study it is important to minimize the sample’s demographic and behavioral variation between the cells or sub-groups. Significant variation can create unusual and unreliable results.
A discrete choice methodology is usually preferable because it is generally more cost effective and provides powerful competitive insight. However, we would strongly recommend using monadic tests under the following specific conditions:
- When testing very specific competitive price scenarios.
- When price is not normally an issue (i.e. physicians)
- When the product attributes are fixed